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Improving the fidelity and performance of a conceptual flood inundation mapping approach using a machine learning-based surrogate model

  • Berina Mina Kilicarslan
  • , Qianqiu Longyang
  • , Victor Obi
  • , Sagy Cohen
  • , Ehab Meselhe
  • , Marouane Temimi
  • Stevens Institute of Technology
  • New York University
  • Arizona State University
  • University of Kansas
  • Kent State University
  • Southern University
  • Department of Geography and the Environment
  • Tulane University

Research output: Contribution to journal › Article › peer-review

3 Scopus citations
1 Downloads (Pure)

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